analytics organizations

Data is a truly inexhaustible resource for an organization. It creates endless possibilities to make data do more. As a technology partner of hundreds of organizations around the world, Infosys helps clients navigate the journey from their current state to the next.
Facilitating clients’ transition into data-native enterprises is a crucial part. To understand how companies are using data analytics today and their expectations in a world of endless possibilities with data, we recently commissioned an independent survey of 1,062 senior executives from organizations with annual revenues exceeding US$ 1 billion, in the United States, Europe, Australia, and New Zealand. The respondents were from business and technology roles, who were decision makers, program managers and external consultants; represented 12 industries, grouped into seven industry clusters, such as, consumer goods, retail and logistics, energy and utilities, financial services and insurance, healthcare and life sciences, h

This report highlights the strategic value of a next generation web content management system integrated with lead scoring, email marketing, customer relationship management, and web analytics. The report links the technology and practices of Best-in-Class organizations to engage customers, provide personalized experiences and manage the lead lifecycle.

To better understand the benefits, costs, and risks associated with implementation of SAP Business Objects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to provide the conclusions of this cost and benefit analysis.

To better understand the benefits, costs, and risks associated with implementation of SAP BusinessObjects Analytics solutions, Forrester interviewed four organizations with multiple years of experience using these analytics solutions from SAP across one or more of the following key analytics areas: planning, business intelligence, and predictive analytics. A composite, or representative, organization was developed to report cost and benefit findings

If your business is like most, you are grappling with data storage. In an annual Frost & Sullivan survey of IT decision-makers, storage growth has been listed among top data center challenges for the past five years.2 With businesses collecting, replicating, and storing exponentially more data than ever before, simply acquiring sufficient storage capacity is a problem.
Even more challenging is that businesses expect more from their stored data. Data is now recognized as a precious corporate asset and competitive differentiator: spawning new business models, new revenue streams, greater intelligence, streamlined operations, and lower costs. Booming market trends such as Internet of Things and Big Data analytics are generating new opportunities faster than IT organizations can prepare for them.

The technology market is giving significant attention to Big Data and analytics as a way to provide insight for decision making support; but how far along is the adoption of these technologies across manufacturing organizations? During a February 2013 survey of over 100 manufacturers we examined behaviors of organizations that measure effective decision making as part of their enterprise performance management efforts. This Analyst Insight paper reveals the results of this survey.

As more enterprises adopt technologies such as cloud, mobile, and analytics to help achieve strategic competitive advantage, CIOs and IT managers must support business-critical processes at a very high level across the enterprise. At the same time, IT organizations must manage complex hybrid IT infrastructures that include both cloud and on-premises technologies from multiple vendors and support providers. IDC believes that to tackle these challenges, IT organizations should look to support
providers for comprehensive offerings to help optimize IT operations and improve the efficiency of IT service delivery. In addition, IDC recommends that IT organizations looking to manage rapid change in today’s IT landscape consider support providers with a record of innovative support services and a focus on advanced technology in support delivery.

Today’s leading-edge organizations differentiate themselves through analytics to further their competitive advantage by extracting value from all their data sources. Other companies are looking to become data-driven through the modernization of their data management deployments. These strategies do include challenges, such as the management of large growing volumes of data. Today’s digital world is already creating data at an explosive rate, and the next wave is on the horizon, driven by the emergence of IoT data sources. The physical data warehouses of the past were great for collecting data from across the enterprise for analysis, but the storage and compute resources needed to support them are not able to keep pace with the explosive growth. In addition, the manual cumbersome task of patch, update, upgrade poses risks to data due to human errors. To reduce risks, costs, complexity, and time to value, many organizations are taking their data warehouses to the cloud. Whether hosted lo

For many of us, the term “smart city” conjures up images of sensors
collecting data about everything from traffic patterns to energy use.
It’s common for government leaders to think, “That’s not for us.
We’re not there yet.” But if your organization is collecting data of any
kind, you are in a position to use that data to create a smarter city for
your citizens.
Download this whitepaper for 10 examples of analytics being used to solve problems or simplify tasks for government organizations.

This RSR custom research report explores the impact of omnichannel methods on merchandising, marketing and the supply chain; specifically, what analytical capabilities address the challenges that omnichannel selling and fulfillment pose for retailers. Consumers today routinely begin their shopping journeys online, but complete their purchases in nearby stores, in their “home” stores or delivered directly to their doors. Retail analytics enables organizations to capture data from their customers' journeys. Retailers that successfully deliver relevant omnichannel experiences while gaining a more sophisticated understanding of demand (where and how it is initiated) will enhance their brands’ value and create compelling and profitable customer relationships.

Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally.
Learn more about key findings, including:
Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics.
Return on investment for analytics stems from the governing and sharing of data throughout the organization.
Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.

This TDWI Best Practices Report focuses on how organizations can and are operationalizing analytics to derive business value. It provides in-depth survey analysis of current strategies and future trends for embedded analytics across both organizational and technical dimensions, including organizational culture, infrastructure, data and processes. It looks at challenges and how organizations are overcoming them, and offers recommendations and best practices for successfully operationalizing analytics in the organization.

Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.

What do these market-defining trends have in common?
· Analytics for all
· Analytics as competitive differentiator
· Internet of Things
· Artificial intelligence/Machine learning/Cognitive computing
· Real-time analytics/event management
They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise?
It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i

Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business, mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace. Customers increasingly drive the speed of business, and organizations need to engage with customers on their terms. The need to manage sensitive information with high levels of security as well as capture, analyze, and act upon massive volumes of data every hour of every day has become critical. These challenges will dramatically change the way that IT systems are designed, funded, and run compared to the past few decades. Databases and Java have become the de facto language in which modern, cloud-ready applications are written. The massive explosion in the volume, variety, and velocity of data increases the need for secure and effective analytics so that organizations can make better

Modern technology initiatives are driving IT infrastructure in a new direction. Big data, social business,
mobile applications, the cloud, and real-time analytics all require forward-thinking solutions and
enough compute power to deliver the performance required in a rapidly evolving digital marketplace.
Customers increasingly drive the speed of business, and organizations need to engage with customers
on their terms. The need to manage sensitive information with high levels of security as well as
capture, analyze, and act upon massive volumes of data every hour of every day has become critical.
These challenges will dramatically change the way that IT systems are designed, funded, and run
compared to the past few decades. Databases and Java have become the de facto language in which
modern, cloud-ready applications are written. The massive explosion in the volume, variety, and
velocity of data increases the need for secure and effective analytics so that organizations can make
better

Databases have long served as the lifeline of the business. Therefore, it is no surprise that performance has always been
top of mind. Whether it be a traditional row-formatted database to handle millions of transactions a day or a columnar
database for advanced analytics to help uncover deep insights about the business, the goal is to service all requests as
quickly as possible. This is especially true as organizations look to gain an edge on their competition by analyzing data
from their transactional (OLTP) database to make more informed business decisions. The traditional model (see Figure
1) for doing this leverages two separate sets of resources, with an ETL being required to transfer the data from the OLTP
database to a data warehouse for analysis. Two obvious problems exist with this implementation. First, I/O bottlenecks
can quickly arise because the databases reside on disk and second, analysis is constantly being done on stale data.
In-memory databases have helped address p

The Internet of Things (IoT) presents an opportunity to collect real-time information about every physical operation of a business. From the temperature of equipment to the performance of a fleet of wind turbines, IoT sensors can deliver this information in real time. There is tremendous opportunity for those businesses that can convert raw IoT data into business insights, and the key to doing so lies within effective data analytics.
To research the current state of IoT analytics, Blue Hill Research conducted deep qualitative interviews with three organizations that invested significant time and resources into their own IoT analytics initiatives. By distilling key themes and lessons learned from peer organizations, Blue Hill Research offers our analysis so that business decision makers can ultimately make informed investment decisions about the future of their IoT analytics projects.

In a panel discussion at the 12th annual SAS Health Analytics
Executive Forum in May 2015, leaders from Dignity Health,
Horizon Blue Cross Blue Shield of New Jersey, Janssen
Pharmaceuticals and SAS shared what they have done to prove
the value of analytics to their business leaders – and what has
worked for them as they developed an analytic culture in their
organizations and put analytic insights to work.

Stories and statistics behind successful analytics projects
The adoption of analytics across the enterprise is accelerating, and with good reason. Analytics can offer a competitive advantage by helping to identify growth opportunities, circumnavigate risk and improve customer relationships. These insights are becoming crucial parts of the business strategy for executives representing a wide array of industries.
Check out our latest eBook to see how some of the world’s leading companies are using analytics to meet their needs. You’ll receive diverse examples of how organizations applied the latest statistical methodologies, such as: scorecard build, regression, decision trees, machine learning and material change to uncover meaning in data.
The examples represent global brands across critical industries – Financial Services, Insurance, High-Tech, Aerospace, Manufacturing and others – where analytics helped answer their most challenging questions.

This paper will explore some of the market dynamics driving the financial volatility in healthcare and will explore how advanced analytics, with the right IT backbone and organizational competencies, can help organizations successfully identify ways to manage revenue cycle profitability.

For an increasing number of organizations, enterprise performance management (EPM) tools are enabling senior finance executives to integrate plans, understand where they're losing money, move from annual budgets to rolling forecasts, and identify opportunities for strategic improvements. During this Webcast, a panel of experts will explore: • Why business intelligence and business analytics are each important to your business; • How Big Data and analytics can help your organization answer more questions and ask even better ones; • The capabilities that enterprise performance management software offers organizations; and • How to evaluate what your organization can gain by implementing enterprise performance management software.

The International Institute of Analytics presents healthcare results from their proprietary assessment tool, The Analytics Benchmark, including measurement of data-related tactical competencies and culture/leadership competencies necessary for data-driven decision-making to become ubiquitous inside organizations. Download this paper to benchmark where your organization stands in the five stages of maturity and the five elements of alignment needed for success.

FICO, a data analytics software company, wanted to diversify into new markets its core offering of providing on-premise software to major corporations. To do this, the company launched FICO Analytic Cloud, a cloud delivery channel that enables FICO to serve organizations of all sizes. FICO Analytic Cloud was first launched in 2013 and provides Platform-as-a-Service (PaaS) access to FICO Decision Management Platform, which allows customers to use FICO tools and technology to create, customize, and deploy applications and services. FICO Decision Management Platform is built on OpenShift Enterprise by Red Hat, which provides the PaaS tools and support FICO needed to rapidly scale the platform and Analytic Cloud.

Download the Keystone Research whitepaper to see how top performing enterprises use their IT investments to store, process, and use data to make more effective, real-time decisions.
Keystone Research, a global economics and data-driven strategy consulting firm, interviewed senior IT and business decision makers at over three hundred businesses to uncover the relationship between Data & Analytics technologies and business performance. This research shows that companies who have developed the most sophisticated Data & Analytics platforms and apply these capabilities as a regular part of their business enjoy operating margins that are eight percentage points higher than lagging organizations. This translates to $100 million in operating profits on average for the more advanced companies in the sample controlling for factors such as company size and industry vertical.